Handle empty input string for embedding models

python/sglang/srt/openai_api/adapter.py

@@ -175,6 +175,32 @@ def guess_chat_template_name_from_model_path(model_path):
         )
 
 
+def _validate_prompt(prompt: str):
+    """Validate that the prompt is not empty or whitespace only."""
+    is_invalid = False
+
+    # Check for empty/whitespace string
+    if isinstance(prompt, str):
+        is_invalid = not prompt.strip()
+    # Check for various invalid list cases: [], [""], [" "], [[]]
+    elif isinstance(prompt, list):
+        is_invalid = not prompt or (
+            len(prompt) == 1
+            and (
+                (isinstance(prompt[0], str) and not prompt[0].strip())
+                or (isinstance(prompt[0], list) and not prompt[0])
+            )
+        )
+
+    if is_invalid:
+        raise HTTPException(
+            status_code=400,
+            detail="Input cannot be empty or contain only whitespace.",
+        )
+
+    return prompt
+
+
 async def v1_files_create(
     file: UploadFile, purpose: str, file_storage_path: str = None
 ):
@@ -1755,6 +1781,8 @@ def v1_embedding_request(all_requests, tokenizer_manager):
 
     for request in all_requests:
         prompt = request.input
+        # Check for empty/whitespace string
+        prompt = _validate_prompt(request.input)
         assert (
             type(prompt) is first_prompt_type
         ), "All prompts must be of the same type in file input settings"

test/srt/test_openai_server.py

@@ -676,6 +676,22 @@ def test_embedding_batch(self):
         self.assertTrue(len(response.data[0].embedding) > 0)
         self.assertTrue(len(response.data[1].embedding) > 0)
 
+    def test_empty_string_embedding(self):
+        """Test embedding an empty string."""
+
+        client = openai.Client(api_key=self.api_key, base_url=self.base_url)
+
+        # Text embedding example with empty string
+        text = ""
+        # Expect a BadRequestError for empty input
+        with self.assertRaises(openai.BadRequestError) as cm:
+            client.embeddings.create(
+                model=self.model,
+                input=text,
+            )
+        # check the status code
+        self.assertEqual(cm.exception.status_code, 400)
+
 
 class TestOpenAIServerIgnoreEOS(CustomTestCase):
     @classmethod